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Strobe sequence design for haplotype assembly

Overview of attention for article published in BMC Bioinformatics, February 2011
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Citations

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Title
Strobe sequence design for haplotype assembly
Published in
BMC Bioinformatics, February 2011
DOI 10.1186/1471-2105-12-s1-s24
Pubmed ID
Authors

Christine Lo, Ali Bashir, Vikas Bansal, Vineet Bafna

Abstract

Humans are diploid, carrying two copies of each chromosome, one from each parent. Separating the paternal and maternal chromosomes is an important component of genetic analyses such as determining genetic association, inferring evolutionary scenarios, computing recombination rates, and detecting cis-regulatory events. As the pair of chromosomes are mostly identical to each other, linking together of alleles at heterozygous sites is sufficient to phase, or separate the two chromosomes. In Haplotype Assembly, the linking is done by sequenced fragments that overlap two heterozygous sites. While there has been a lot of research on correcting errors to achieve accurate haplotypes via assembly, relatively little work has been done on designing sequencing experiments to get long haplotypes. Here, we describe the different design parameters that can be adjusted with next generation and upcoming sequencing technologies, and study the impact of design choice on the length of the haplotype.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
France 2 3%
Italy 1 2%
Norway 1 2%
United Kingdom 1 2%
China 1 2%
Germany 1 2%
Unknown 50 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 31%
Researcher 16 27%
Other 5 8%
Professor > Associate Professor 5 8%
Student > Master 4 7%
Other 10 17%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 36 61%
Computer Science 12 20%
Biochemistry, Genetics and Molecular Biology 5 8%
Unspecified 1 2%
Mathematics 1 2%
Other 2 3%
Unknown 2 3%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 June 2011.
All research outputs
#3,108,591
of 4,506,407 outputs
Outputs from BMC Bioinformatics
#2,181
of 2,646 outputs
Outputs of similar age
#2,400,346
of 3,441,809 outputs
Outputs of similar age from BMC Bioinformatics
#2,070
of 2,517 outputs
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